Arrow Research search

Author name cluster

Stephen Cranefield

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

27 papers
2 author rows

Possible papers

27

AAMAS Conference 2024 Conference Paper

Generating and Choosing Organizations for Multi-Agent Systems

  • Cleber J. Amaral
  • Jomi F. Hübner
  • Stephen Cranefield

The design of organizations is a complex and laborious task. It is the subject of recent studies, which define models to automatically perform this task. However, existing models constrain the space of possible solutions by requiring a priori definitions of organizational roles and usually are not suitable for planning resource use. This paper presents GoOrg [1], a model that uses as input a set of goals and a set of available agents to generate different arrangements of organizational structures made up of synthesized organizational positions. The most distinguishing characteristics of GoOrg are the use of organizational positions instead of roles and that positions are automatically synthesized rather than required as a priori defined inputs. These features allow for the planning of organizational resources at design time and increase the chance of finding feasible solutions. This paper also introduces a model extension that illustrates how GoOrg can be extended to suit a specific domain.

PDF

AAMAS Conference 2024 Conference Paper

Inferring Lewisian Common Knowledge using Theory of Mind Reasoning in a Forward-chaining Rule Engine

  • Stephen Cranefield
  • Sriashalya Srivathsan
  • Jeremy Pitt

This paper presents a practical technique for inferring common knowledge based on the approach of David Lewis, who identified three conditions that are sufficient for information about the world and other agents’ reasoning mechanisms to lead to chains of iterated mutual knowledge. We consider agents with theory-of-mind rules that model other agents’ beliefs. We prove that only two levels of nested models of other agents are necessary to achieve common knowledge. We illustrate this approach with an implemented scenario involving information on monuments in a public forum.

PDF

IJCAI Conference 2023 Conference Paper

Cross-community Adapter Learning (CAL) to Understand the Evolving Meanings of Norm Violation

  • Thiago Freitas dos Santos
  • Stephen Cranefield
  • Bastin Tony Roy Savarimuthu
  • Nardine Osman
  • Marco Schorlemmer

Cross-community learning incorporates data from different sources to leverage task-specific solutions in a target community. This approach is particularly interesting for low-resource or newly created online communities, where data formalizing interactions between agents (community members) are limited. In such scenarios, a normative system that intends to regulate online interactions faces the challenge of continuously learning the meaning of norm violation as communities' views evolve, either with changes in the understanding of what it means to violate a norm or with the emergence of new violation classes. To address this issue, we propose the Cross-community Adapter Learning (CAL) framework, which combines adapters and transformer-based models to learn the meaning of norm violations expressed as textual sentences. Additionally, we analyze the differences in the meaning of norm violations between communities, using Integrated Gradients (IG) to understand the inner workings of our model and calculate a global relevance score that indicates the relevance of words for violation detection. Results show that cross-community learning enhances CAL's performance while explaining the differences in the meaning of norm-violating behavior based on community members' feedback. We evaluate our proposal in a small set of interaction data from Wikipedia, in which the norm prohibits hate speech.

PDF Details DOI

JAAMAS Journal 2023 Journal Article

Generating and choosing organisations for multi-agent systems

  • Cleber J. Amaral
  • Jomi F. Hübner
  • Stephen Cranefield

Abstract The design of organisations is a complex and laborious task. It is the subject of recent studies, which define models to automatically perform this task. However, existing models constrain the space of possible solutions by requiring a priori definitions of organisational roles and usually are not suitable for planning resource use. This paper presents GoOrg, a model that uses as input a set of goals and a set of available agents to generate different arrangements of organisational structures made up of synthesised organisational positions. The most distinguishing characteristics of GoOrg are the use of organisational positions instead of roles and that positions are automatically synthesised rather than required as a priori defined inputs. These characteristics facilitate the parametrisation, the use for resource planning and the chance of finding feasible solutions. This paper also introduces two model extensions, which define processes and constraints that illustrate how GoOrg suits different domains. Among aspects that surround an organisation design, this paper discusses models’ input, agents’ abstractions and resource planning.

Details DOI

JAAMAS Journal 2021 Journal Article

Enabling BDI group plans with coordination middleware: semantics and implementation

  • Stephen Cranefield

Abstract This paper investigates the use of group goals and plans as programming abstractions that provide explicit constructs for goals and plans involving coordinated action by groups of agents, with a focus on the BDI agent model. We define a group goal construct, which specifies subgoals that the group members must satisfy for the group goal to succeed, subject to timeouts on the members beginning work on the goal, and then completing their subgoals. A group plan containing one or more group goals can be dynamically distributed amongst a set of agents and jointly executed without a need for explicit coordinating communication between agents. We define formal semantics that model the coordination needed to determine a group goal’s success or failure as updates to a shared state machine for the group goal. We implement the semantics directly as rewrite rules in Maude, and verify using LTL model checking that the intended coordination behaviour is achieved. An implementation of group plans and goals for the Jason agent platform is also described, based on an integration of Jason with the ZooKeeper coordination middleware via a set of generic Jason plans supporting group goals, and the Apache Camel integration framework. A evaluation of the performance of this implementation is presented, showing that the approach is scalable.

Details DOI

IJCAI Conference 2021 Conference Paper

Identifying Norms from Observation Using MCMC Sampling

  • Stephen Cranefield
  • Ashish Dhiman

To promote efficient interactions in dynamic and multi-agent systems, there is much interest in techniques that allow agents to represent and reason about social norms that govern agent interactions. Much of this work assumes that norms are provided to agents, but some work has investigated how agents can identify the norms present in a society through observation and experience. However, the norm-identification techniques proposed in the literature often depend on a very specific and domain-specific representation of norms, or require that the possible norms can be enumerated in advance. This paper investigates the problem of identifying norm candidates from a normative language expressed as a probabilistic context-free grammar, using Markov Chain Monte Carlo (MCMC) search. We apply our technique to a simulated robot manipulator task and show that it allows effective identification of norms from observation.

PDF Details DOI

AAMAS Conference 2019 Conference Paper

On Enactability of Agent Interaction Protocols: Towards a Unified Approach

  • Angelo Ferrando
  • Michael Winikoff
  • Stephen Cranefield
  • Frank Dignum
  • Viviana Mascardi

Interactions between agents are usually designed from a global viewpoint. However, the implementation of a multi-agent interaction is distributed. This difference can introduce problems. For instance, it is possible to specify protocols from a global viewpoint that cannot be implemented as a collection of individual agents. This leads naturally to the question of whether a given (global) protocol is enactable. We consider this question in a powerful setting (trace expressions), considering a range of message ordering interpretations (specifying what it means to say that an interaction step occurs before another), and a range of possible constraints on the semantics of message delivery, corresponding to different properties of the underlying communication middleware.

PDF

IJCAI Conference 2017 Conference Paper

No Pizza for You: Value-based Plan Selection in BDI Agents

  • Stephen Cranefield
  • Michael Winikoff
  • Virginia Dignum
  • Frank Dignum

Autonomous agents are increasingly required to be able to make moral decisions. In these situations, the agent should be able to reason about the ethical bases of the decision and explain its decision in terms of the moral values involved. This is of special importance when the agent is interacting with a user and should understand the value priorities of the user in order to provide adequate support. This paper presents a model of agent behavior that takes into account user preferences and moral values.

PDF Details

ECAI Conference 2016 Conference Paper

A Bayesian Approach to Norm Identification

  • Stephen Cranefield
  • Felipe Meneguzzi
  • Nir Oren
  • Bastin Tony Roy Savarimuthu

When entering a system, an agent should be aware of the obligations and prohibitions (collectively norms) that affect it. Existing solutions to this norm identification problem make use of observations of either norm compliant, or norm violating, behaviour. Thus, they assume an extreme situation where norms are typically violated, or complied with. In this paper we propose a Bayesian approach to norm identification which operates by learning from both norm compliant and norm violating behaviour. We evaluate our approach's effectiveness empirically and compare its accuracy to existing approaches. By utilising both types of behaviour, we not only overcome a major limitation of such approaches, but also obtain improved performance over the state of the art, allowing norms to be learned with fewer observations.

Details

AAMAS Conference 2016 Conference Paper

Supporting Group Plans in the BDI Architecture Using Coordination Middleware (Extended Abstract)

  • Stephen Cranefield

This paper investigates the use of group plans and goals as programming abstractions that encapsulate the communication needed to coordinate collaborative behaviour. It presents an extension of the BDI agent architecture to include explicit constructs for goals and plans that involve coordinated action by groups of agents. Formal operational semantics for group goals are outlined, and an implementation of group plans and goals for the Jason agent platform, based on integration with the ZooKeeper coordination middleware, is described.

PDF

IJCAI Conference 2015 Conference Paper

On the Testability of BDI Agent Systems (Extended Abstract)

  • Michael Winikoff
  • Stephen Cranefield

Before deploying a software system we need to assure ourselves (and stakeholders) that the system will behave correctly. This assurance is usually done by testing the system. However, it is intuitively obvious that adaptive systems, including agent-based systems, can exhibit complex behaviour, and are thus harder to test. In this paper we examine this “obvious intuition” in the case of Belief-Desire-Intention (BDI) agents, by analysing the number of paths through BDI goalplan trees. Our analysis confirms quantitatively that BDI agents are hard to test, sheds light on the role of different parameters, and highlights the enormous difference made by failure handling.

PDF Details

AAMAS Conference 2013 Conference Paper

Embedding Agents in Business Applications Using Enterprise Integration Patterns

  • Stephen Cranefield
  • Surangika Ranathunga

This paper addresses the integration of agents with external resources and services in enterprise computing environments. We propose an approach for interfacing agents and existing message routing and mediation engines based on the endpoint concept from the enterprise integration patterns of Hohpe and Woolf.

PDF

AAMAS Conference 2012 Conference Paper

Expectation and Complex Event Handling in BDI-based Intelligent Virtual Agents

  • Surangika Ranathunga
  • Stephen Cranefield

When operating in virtual communities, intelligent agents should maintain a high-level awareness of the physical and social environment around them in order to be more believable and capable. However, due to the inherent differences between virtual worlds and agent systems such as BDI, such a high-level of awareness has not been achieved for IVAs. In this paper we present a system that enables IVAs to maintain a high-level awareness of their environment by identifying complex events taking place in their environment, as well as by being able to monitor for the fulfilment and violation of their expectations.

PDF

AILAW Journal 2012 Journal Article

Identifying prohibition norms in agent societies

  • Bastin Tony Roy Savarimuthu
  • Stephen Cranefield
  • Maryam A. Purvis
  • Martin K. Purvis

Abstract In normative multi-agent systems, the question of “how an agent identifies norms in an open agent society” has not received much attention. This paper aims at addressing this question. To this end, this paper proposes an architecture for norm identification for an agent. The architecture is based on observation of interactions between agents. This architecture enables an autonomous agent to identify prohibition norms in a society using the prohibition norm identification (PNI) algorithm. The PNI algorithm uses association rule mining, a data mining approach to identify sequences of events as candidate norms. When a norm changes, an agent using our architecture will be able to modify the norm and also remove a norm if it does not hold in the society. Using simulations of a park scenario we demonstrate how an agent makes use of the norm identification framework to identify prohibition norms.

Details DOI

AAMAS Conference 2011 Conference Paper

Agent-Based Container Terminal Optimisation

  • Stephen Cranefield
  • Roger Jarquin
  • Guannan Li
  • Brent Martin
  • Rainer Unland
  • Hanno-Felix Wagner
  • Michael Winikoff
  • Thomas Young

Container terminals play a critical role in international shipping and are under pressure to cope with increasing container traffic. The problem of managing container terminals effectively has a number of characteristics that suggest the use of agent technology would be beneficial. This paper describes a joint industry-university project which has explored the applicability of agent technology to the domain of container terminal management.

PDF

AAMAS Conference 2011 Conference Paper

Interfacing a Cognitive Agent Platform with a Virtual World: a Case Study using Second Life

  • Surangika Ranathunga
  • Stephen Cranefield
  • MARTIN PURVIS

Online virtual worlds provide a rich platform for remote human interaction, and are increasingly being used as a simulation platform for multi-agent systems and as a way for software agents to interact with humans. It would therefore be beneficial to provide techniques allowing high-level agent development tools, especially cognitive agent platforms such as belief-desire-intention (BDI) programming frameworks, to be interfaced with virtual worlds. This is not a trivial task as it involves mapping potentially unreliable sensor readings from complex virtual environments to a domain-specific abstract logical model of observed properties and/or events. This paper investigates this problem in the context of agent interactions in a multi-agent system simulated in Second Life. We present a framework which facilitates the connection of any multi-agent platform with Second Life, and demonstrate it in conjunction with the Jason BDI interpreter.

PDF

AAMAS Conference 2010 Conference Paper

A Social-Network Defense against Whitewashing

  • Adrian Perreau de Pinninck
  • Marco Schorlemmer
  • Carles Sierra
  • Stephen Cranefield

We provide a defence against whitewashing for trust assessment mechanisms (TAM) by using an underlying social network in MAS and P2P. Since interaction requests are routedthrough the social network, routers can block requests fromportions of the network known for whitewashing. Furthermore, by limiting feedback spread to the interaction routers, the trust assessment can be done without querying for feedback with a small loss in efficiency.

PDF

KER Journal 2002 Journal Article

A UML profile and mapping for the generation of ontology-specific content languages

  • Stephen Cranefield
  • MARTIN PURVIS

This paper examines a perceived desire amongst software agent application and platform developers to have the ability to send domain-specific objects within inter-agent messages. If this feature is to be supported without departing from the notion that agents communicate in terms of knowledge, it is important that the meaning of such objects be well defined. Using an object-oriented metamodelling approach, the relationships between ontologies and agent communication and content languages in FIPA-style agent systems are examined. It is argued that for use with distributed multi-agent systems, ontologies should describe the nature of object identity and reference for each defined concept, and a UML profile supporting these modelling capabilities is presented. Finally it is shown how, given an ontology in UML, an ontology-specific object-oriented content language can be generated, allowing object structures (viewed in the abstract as UML object diagrams) to be used within message content to represent propositions, definite descriptions or (for classes without identity) value expressions.

Details DOI

KER Journal 2002 Journal Article

Introduction to the special issue on ontologies in agent systems

  • Stephen Cranefield
  • STEVEN WILLMOTT
  • Tim Finin

It is now more than ten years since researchers in the US Knowledge Sharing Effort envisaged a future where complex systems could be built by combining knowledge and services from multiple knowledge bases and the first agent communication language, KQML, was proposed (Neches et al., 1991). This model of communication, based on speech acts, a declarative message content representation language and the use of explicit ontologies defining the domains of discourse (Genesereth & Ketchpel, 1994), has become widely recognised as having great benefits for the integration of disparate and distributed information sources to form an open, extensible and loosely coupled system. In particular, this idea has become a key tenet in the multi-agent systems research community.

Details DOI

KER Journal 2002 Journal Article

UML for ontology development

  • PAUL KOGUT
  • Stephen Cranefield
  • LEWIS HART
  • MARK DUTRA
  • KENNETH BACLAWSKI
  • MIECZYSLAW KOKAR
  • JEFFREY SMITH

Ontologies are becoming increasingly important because they provide the critical semantic foundation for many rapidly expanding technologies such as software agents, e-commerce and knowledge management (McGuinness, 2002). The Unified Modelling Language (UML)1 has been widely adopted by the software engineering community and its scope is broadening to include more diverse modelling tasks. This paper discusses the recent convergence of UML and ontologies and suggests some possible future directions.

Details DOI